Mendizábal Aizpuru, José Antonio
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Mendizábal Aizpuru
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José Antonio
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Agronomía, Biotecnología y Alimentación
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IS-FOOD. Research Institute on Innovation & Sustainable Development in Food Chain
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Publication Open Access Volatile compounds, odour and flavour attributes of lamb meat from the navarra breed as affected by ageing(MDPI, 2021) Insausti Barrenetxea, Kizkitza; Urrutia Vera, Olaia; Mendizábal Aizpuru, José Antonio; Beriain Apesteguía, María José; Colle, Michael J.; Bass, Phillip D.; Arana Navarro, Ana; Murillo Arbizu, María Teresa; Institute on Innovation and Sustainable Development in Food Chain - ISFOODThis study aimed to assess the influence of ageing on the volatile compounds, as well as odour and flavour attributes of lamb meat from the Navarra breed. Twenty-one male lambs were fed a commercial concentrate diet after weaning and were harvested at 101 ± 6.5 days of age. From the Longissimus thoracis, 26 volatile compounds were identified, with hexanal, 2-propanone, and nonanal the most abundant (57.17% relative percentage abundance, RPA). The effect of ageing (1 vs. 4 d) was observed (p < 0.05) in six compounds: 1,4-dimethylbenzene decreased with ageing, while tridecane, 3-methylbutanal, 2-heptanone, 3-octanone, and 1-octen-3-ol increased. In general, ageing was linked to a decrease in livery and bloody flavour, bloody odour and ethanal, and an increase in pentane, hexanal, and heptanal, which are usually associated with fresh green grass and fat descriptors. Consequently, ageing lamb from the Navarra breed for four days might have a positive effect on meat sensory odour and flavour quality.Publication Open Access Classification of beef longissimus thoracis muscle tenderness using hyperspectral imaging and chemometrics(MDPI, 2022) León Ecay, Sara; López Maestresalas, Ainara; Murillo Arbizu, María Teresa; Beriain Apesteguía, María José; Mendizábal Aizpuru, José Antonio; Arazuri Garín, Silvia; Jarén Ceballos, Carmen; Bass, Phillip D.; Colle, Michael J.; García, David; Romano Moreno, Miguel; Insausti Barrenetxea, Kizkitza; Agronomia, Bioteknologia eta Elikadura; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Agronomía, Biotecnología y Alimentación; Ingeniería; Gobierno de Navarra / Nafarroako Gobernua Universidad Pública de Navarra / Nafarroako UnibertsitateNowadays, the meat industry requires non-destructive, sustainable, and rapid methods that can provide objective and accurate quality assessment with little human intervention. Therefore, the present research aimed to create a model that can classify beef samples from longissimus thoracis muscle according to their tenderness degree based on hyperspectral imaging (HSI). In order to obtain different textures, two main strategies were used: (a) aging type (wet and dry aging with or without starters) and (b) aging times (0, 7, 13, 21, and 27 days). Categorization into two groups was carried out for further chemometric analysis, encompassing group 1 (ngroup1 = 30) with samples with WBSF < 53 N whereas group 2 (ngroup2 = 28) comprised samples with WBSF values 53 N. Then, classification models were created by applying the partial least squares discriminant analysis (PLS-DA) method. The best results were achieved by combining the following pre-processing algorithms: 1st derivative + mean center, reaching 70.83% of correctly classified (CC) samples and 67.14% for cross validation (CV) and prediction, respectively. In general, it can be concluded that HSI technology combined with chemometrics has the potential to differentiate and classify meat samples according to their textural characteristics.